Shashi Jangra et al, International Journal of Computer Science and Mobile Computing, Vol.3 Issue.5, May- 2014, pg. 454-457 © 2014, IJCSMC All Rights Reserved 454 Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology ISSN 2320–088X IJCSMC, Vol. 3, Issue. 5, May 2014, pg.454 – 457 REVIEW ARTICLE A Review of Rician Noise Reduction in MRI Images using Wave Atom Transform 1 Shashi Jangra, 2 Mr. Samit Yadav 1 M.Tech Scholar in CSE GITAM, Kablana, Haryana shashijangra21@gmail.com 2 Guide, AP in GITAM, Kablana, Haryana samit1981@gmail.com Abstract : Magnetic resonance imaging is a medical imaging technique that measures the response of atomic nuclei of body tissues to high frequency radio waves when placed in a strong magnetic field and that produces images of the internal organs. De-noising is always a challenging problem in magnetic resonance imaging and important for clinical diagnosis and computerized analysis, such as tissue classification and segmentation. It is well known that the noise in magnetic resonance imaging has a Rician distribution. . In this paper, an improved de-noising technique is proposed on Magnetic Resonance Images highly corrupted with Rician Noise using wave atom shrinkage. General Terms Clinical diagnosis, tissue classification, segmentation Keywords De-noising, Histogram, Magnetic Resonance Image, Rician Noise, Variance Estimation, Wave Atom Transform I. INTRODUCTION Wave atoms are a recent addition to the repertoire of mathematical transforms of computational harmonic analysis. They come either as an orthonormal basis or a tight frame of directional wave packets, and are particularly well suited for representing oscillatory patterns in images. They also provide a sparse representation of wave equations, hence the name wave atoms [1]. Magnetic Resonance Imaging (MRI) is a notable medical imaging technique that has proven to be particularly valuable for examination of the soft tissues in the body. MRI is primarily used to demonstrate pathological or other physiological alterations of living tissues and is a commonly used form of medical imaging. Because of the resolution of MRI and the technology being essentially harmless it has emerged as the most accurate and desirable imaging technology [2]. Despite significant improvements in recent years, magnetic resonance (MR) images often suffer from low Signal to Noise Ratio (SNR) especially in brain imaging. This paper presents an improved multi resolution de-noising method to de- noise Magnetic Resonance Images using Wave Atom Shrinkage, histogram based noise variance estimation [3] and modified threshold calculation that leads to the improvement of SNR in high noise level images. The paper is organized with sections as follows. In section 2, the work related to this paper is briefly explained, Section 3 briefly explained about the rician noise which is usually present in MRI, Section 4 deals with the explanation of the estimation of rician noise variance, used in this method, In section 5, the theoretical concepts of wave atom transforms is described, in section 6, the application of wave atom transform and wavelet transforms to MRI and observations are discussed. In section 7, the paper is concluded by briefly explained the pros and corns of the proposed method.